Data resolution system for management of distributed data

ABSTRACT

System and methods are described for management of distributed data. In one implementation, a data resolution system receives a data resolution request from a data consumer. The system then identifies data sources based on a schema registry, and queries each of the data sources for data corresponding to the expressions. The system then generates a hydrated data object comprising the received data, and transmits the hydrated data object to the data consumer.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the United States Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.

TECHNICAL FIELD

One or more implementations relate to distributed data systems, and more specifically to resolution of data distributed across multiple data sources.

BACKGROUND

“Cloud computing” services provide shared resources, software, and information to computers and other devices upon request or on demand. Cloud computing typically involves the over-the-Internet provision of dynamically-scalable and often virtualized resources. Technological details can be abstracted from end-users, who no longer have need for expertise in, or control over, the technology infrastructure “in the cloud” that supports them. In cloud computing environments, software applications can be accessible over the Internet rather than installed locally on personal or in-house computer systems. Some of the applications or on-demand services provided to end-users can include the ability for a user to create, view, modify, store and share documents and other files.

Distributed data is often needed by a single system to perform specialized operations, such as preparing customized content and generating emails, but such data is typically stored in multiple remote systems. A common approach to solve this problem is to replicate data between data centers. However, this approach is expensive both in terms of money and in terms of network and computing resources. Moreover, it also introduces new problems related to data synchronization and can make it difficult to determine which system is the system of record.

BRIEF DESCRIPTION OF THE DRAWINGS

The included drawings are for illustrative purposes and serve to provide examples of possible structures and operations for the disclosed inventive systems, apparatus, methods, and computer-readable storage media. These drawings in no way limit any changes in form and detail that may be made by one skilled in the art without departing from the spirit and scope of the disclosed implementations.

FIG. 1A shows a block diagram of an example environment in which an on-demand database service can be used according to some implementations.

FIG. 1B shows a block diagram of example implementations of elements of FIG. 1A and example interconnections between these elements according to some implementations.

FIG. 2A shows a system diagram of example architectural components of an on-demand database service environment according to some implementations.

FIG. 2B shows a system diagram further illustrating example architectural components of an on-demand database service environment according to some implementations.

FIG. 3 illustrates a diagrammatic representation of a machine in the exemplary form of a computer system within which one or more implementations may be carried out.

FIG. 4 is a system topology diagram illustrating the interplay between various systems according to some implementations.

FIG. 5 is a sequence diagram illustrating data resolution according to some implementations.

FIG. 6 is a flow diagram illustrating a method for performing data resolution according to some implementations.

DETAILED DESCRIPTION

The implementations described herein relate to data resolution for the management of distributed data. Distributed data is often utilized by a single system to perform specialized operations (e.g., preparing customized content, generating emails, etc.), but the desired data is typically stored across multiple remote systems. A common approach to mitigate this problem is to replicate data between data centers; however, this approach is expensive monetarily and in terms of network and computing resources. Moreover, this approach also introduces new problems, such as data synchronization, and can make determining which system is the system of record more difficult. End users of the data must also know exactly on which systems the data exists, and must often design schemas in multiple systems to synchronize data between systems.

The implementations described herein allow for the management of data sources and schemas across multiple systems and the orchestration of the resolution of data resolution expressions to facilitate movement of data between several applications and physical data centers. The implementations focus less on the internals of each system's data store, and instead focus more on what it is that is requested and how to retrieve it when it is needed.

Certain aspects of the present implementations include a design time aspect (i.e., indicating to a data resolution system what will be asked) and a runtime aspect (i.e., the data resolution system actually requests the data to be queried). In certain implementations, expressions mapping to data source objects are defined at design time and the data is not queried until runtime. For example, a data consumer may require the first and last name of a customer for when emails are be sent to that customer, but the actual values do not need to be resolved until runtime when the email is generated and sent. In certain implementations, prior to when an application utilized by the data consumer requires the data, a data request is made to the data resolution system at runtime, which proxies the requests to other systems and then returns a single hydrated object back to the requesting application. In certain implementations, the responsibility of data transformation is performed by a data resolution system, rather than by a consuming application. The consuming application may request specific data that it needs at runtime rather than query the entire data set. In certain implementations, if a data source system must perform ETL to prepare the data, then such logic may be handled by the data source system, and not the data consumer. In other words, in such implementations it is the responsibility of the data source system to provide the data values that are requested of it. The implementations described herein may also be used to manage system-to-system schemas so that users are not required to manage a logical data layer and mappings to physical data storage.

Advantages of the implementations of the disclosure over traditional approaches include, but are not limited to: (1) coordination of data between multiple systems that have different underlying architectures, data stores, and application logic; (2) requesting data at runtime or close to a time that an application needs the data to execute logic, rather than at design time; (3) avoiding or at least minimizing data replication (which requires the same schema and types of database technology across systems) and data synchronization (which is prone to latency and in turn results in stale data requiring user intervention); and (4) providing a schema management paradigm that abstracts the schema from data sources of the underlying implementation.

As used herein, the term “schema” refers to a data structure representative of a database that defines how the data is organized, the logical relationships between the data, and constraints applied to the data.

As used herein, the term “data resolution expression” refers to an expression derived from a data resolution schema that is used by data resolution nodes to query values.

As used herein, the term “data resolution request” refers to a request that includes a data object having fields with expressions that identify data or types of data requested by a data consumer.

As used herein, the term “data consumer” refers to any device that requests data for use before or during runtime of an application.

Examples of systems, apparatuses, computer-readable storage media, and methods according to the disclosed implementations are described in this section. These examples are being provided solely to add context and aid in the understanding of the disclosed implementations. It will thus be apparent to one skilled in the art that the disclosed implementations may be practiced without some or all of the specific details provided. In other instances, certain process or method operations, also referred to herein as “blocks,” have not been described in detail in order to avoid unnecessarily obscuring the disclosed implementations. Other implementations and applications also are possible, and as such, the following examples should not be taken as definitive or limiting either in scope or setting.

In the following detailed description, references are made to the accompanying drawings, which form a part of the description and in which are shown, by way of illustration, specific implementations. Although these disclosed implementations are described in sufficient detail to enable one skilled in the art to practice the implementations, it is to be understood that these examples are not limiting, such that other implementations may be used and changes may be made to the disclosed implementations without departing from their spirit and scope. For example, the blocks of the methods shown and described herein are not necessarily performed in the order indicated in some other implementations. Additionally, in some other implementations, the disclosed methods may include more or fewer blocks than are described. As another example, some blocks described herein as separate blocks may be combined in some other implementations. Conversely, what may be described herein as a single block may be implemented in multiple blocks in some other implementations. Additionally, the conjunction “or” is intended herein in the inclusive sense where appropriate unless otherwise indicated; that is, the phrase “A, B, or C” is intended to include the possibilities of “A,” “B,” “C,” “A and B,” “B and C,” “A and C,” and “A, B, and C.”

The words “example” or “exemplary” are used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “example” or “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the words “example” or “exemplary” is intended to present concepts in a concrete fashion.

In addition, the articles “a” and “an” as used herein and in the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form. Reference throughout this specification to “an implementation,” “one implementation,” “some implementations,” or “certain implementations” indicates that a particular feature, structure, or characteristic described in connection with the implementation is included in at least one implementation. Thus, the appearances of the phrase “an implementation,” “one implementation,” “some implementations,” or “certain implementations” in various locations throughout this specification are not necessarily all referring to the same implementation.

Some portions of the detailed description may be presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the manner used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is herein, and generally, conceived to be a self-consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, or otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as “receiving,” “retrieving,” “transmitting,” “computing,” “generating,” “adding,” “subtracting,” “multiplying,” “dividing,” “optimizing,” “calibrating,” “detecting,” “performing,” “analyzing,” “determining,” “enabling,” “identifying,” “modifying,” “transforming,” “applying,” “aggregating,” “extracting,” “registering,” “querying,” “populating,” “hydrating,” “updating,” or the like, refer to the actions and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (e.g., electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission, or display devices.

The specific details of the specific aspects of implementations disclosed herein may be combined in any suitable manner without departing from the spirit and scope of the disclosed implementations. However, other implementations may be directed to specific implementations relating to each individual aspect, or specific combinations of these individual aspects. Additionally, while the disclosed examples are often described herein with reference to an implementation in which an on-demand database service environment is implemented in a system having an application server providing a front end for an on-demand database service capable of supporting multiple tenants, the present implementations are not limited to multi-tenant databases or deployment on application servers. Implementations may be practiced using other database architectures, i.e., ORACLE®, DB2® by IBM, and the like without departing from the scope of the implementations claimed. Moreover, the implementations are applicable to other systems and environments including, but not limited to, client-server models, mobile technology and devices, wearable devices, and on-demand services.

It should also be understood that some of the disclosed implementations can be embodied in the form of various types of hardware, software, firmware, or combinations thereof, including in the form of control logic, and using such hardware or software in a modular or integrated manner. Other ways or methods are possible using hardware and a combination of hardware and software. Any of the software components or functions described in this application can be implemented as software code to be executed by one or more processors using any suitable computer language such as, for example, C, C++, Java™ (which is a trademark of Sun Microsystems, Inc.), or Perl using, for example, existing or object-oriented techniques. The software code can be stored as non-transitory instructions on any type of tangible computer-readable storage medium (referred to herein as a “non-transitory computer-readable storage medium”). Examples of suitable media include random access memory (RAM), read-only memory (ROM), magnetic media such as a hard-drive or a floppy disk, or an optical medium such as a compact disc (CD) or digital versatile disc (DVD), flash memory, and the like, or any combination of such storage or transmission devices. Computer-readable media encoded with the software/program code may be packaged with a compatible device or provided separately from other devices (for example, via Internet download). Any such computer-readable medium may reside on or within a single computing device or an entire computer system, and may be among other computer-readable media within a system or network. A computer system, or other computing device, may include a monitor, printer, or other suitable display for providing any of the results mentioned herein to a user.

The disclosure also relates to apparatuses, devices, and system adapted/configured to perform the operations herein. The apparatuses, devices, and systems may be specially constructed for their required purposes, may be selectively activated or reconfigured by a computer program, or some combination thereof.

I. Example System Overview

FIG. 1A shows a block diagram of an example of an environment 10 in which an on-demand database service can be used in accordance with some implementations. The environment 10 includes user systems 12, a network 14, a database system 16 (also referred to herein as a “cloud-based system”), a processor system 17, an application platform 18, a network interface 20, tenant database 22 for storing tenant data 23, system database 24 for storing system data 25, program code 26 for implementing various functions of the database system 16, and process space 28 for executing database system processes and tenant-specific processes, such as running applications as part of an application hosting service. In some other implementations, environment 10 may not have all of these components or systems, or may have other components or systems instead of, or in addition to, those listed above.

In some implementations, the environment 10 is an environment in which an on-demand database service exists. An on-demand database service, such as that which can be implemented using the database system 16, is a service that is made available to users outside an enterprise (or enterprises) that owns, maintains, or provides access to the database system 16. As described above, such users generally do not need to be concerned with building or maintaining the database system 16. Instead, resources provided by the database system 16 may be available for such users' use when the users need services provided by the database system 16; that is, on the demand of the users. Some on-demand database services can store information from one or more tenants into tables of a common database image to form a multi-tenant database system (MTS). The term “multi-tenant database system” can refer to those systems in which various elements of hardware and software of a database system may be shared by one or more customers or tenants. For example, a given application server may simultaneously process requests for a great number of customers, and a given database table may store rows of data such as feed items for a potentially much greater number of customers. A database image can include one or more database objects. A relational database management system (RDBMS) or the equivalent can execute storage and retrieval of information against the database object(s).

Application platform 18 can be a framework that allows the applications of the database system 16 to execute, such as the hardware or software infrastructure of the database system 16. In some implementations, the application platform 18 enables the creation, management and execution of one or more applications developed by the provider of the on-demand database service, users accessing the on-demand database service via user systems 12, or third party application developers accessing the on-demand database service via user systems 12.

In some implementations, the database system 16 implements a web-based customer relationship management (CRM) system. For example, in some such implementations, the database system 16 includes application servers configured to implement and execute CRM software applications as well as provide related data, code, forms, renderable web pages, and documents and other information to and from user systems 12 and to store to, and retrieve from, a database system related data, objects, and Web page content. In some MTS implementations, data for multiple tenants may be stored in the same physical database object in tenant database 22. In some such implementations, tenant data is arranged in the storage medium(s) of tenant database 22 so that data of one tenant is kept logically separate from that of other tenants so that one tenant does not have access to another tenant's data, unless such data is expressly shared. The database system 16 also implements applications other than, or in addition to, a CRM application. For example, the database system 16 can provide tenant access to multiple hosted (standard and custom) applications, including a CRM application. User (or third party developer) applications, which may or may not include CRM, may be supported by the application platform 18. The application platform 18 manages the creation and storage of the applications into one or more database objects and the execution of the applications in one or more virtual machines in the process space of the database system 16.

According to some implementations, each database system 16 is configured to provide web pages, forms, applications, data, and media content to user (client) systems 12 to support the access by user systems 12 as tenants of the database system 16. As such, the database system 16 provides security mechanisms to keep each tenant's data separate unless the data is shared. If more than one MTS is used, they may be located in close proximity to one another (for example, in a server farm located in a single building or campus), or they may be distributed at locations remote from one another (for example, one or more servers located in city A and one or more servers located in city B). As used herein, each MTS could include one or more logically or physically connected servers distributed locally or across one or more geographic locations. Additionally, the term “server” is meant to refer to a computing device or system, including processing hardware and process space(s), an associated storage medium such as a memory device or database, and, in some instances, a database application, such as an object-oriented database management system (OODBMS) or a relational database management system (RDBMS), as is well known in the art. It should also be understood that “server system” and “server” are often used interchangeably herein. Similarly, the database objects described herein can be implemented as part of a single database, a distributed database, a collection of distributed databases, a database with redundant online or offline backups or other redundancies, etc., and can include a distributed database or storage network and associated processing intelligence.

The network 14 can be or include any network or combination of networks of systems or devices that communicate with one another. For example, the network 14 can be or include any one or any combination of a local area network (LAN), wide area network (WAN), telephone network, wireless network, cellular network, point-to-point network, star network, token ring network, hub network, or other appropriate configuration. The network 14 can include a Transfer Control Protocol and Internet Protocol (TCP/IP) network, such as the global internetwork of networks often referred to as the “Internet” (with a capital “I”). The Internet will be used in many of the examples herein. However, it should be understood that the networks that the disclosed implementations can use are not so limited, although TCP/IP is a frequently implemented protocol.

The user systems 12 can communicate with the database system 16 using TCP/IP and, at a higher network level, other common Internet protocols to communicate, such as the Hyper Text Transfer Protocol (HTTP), Hyper Text Transfer Protocol Secure (HTTPS), File Transfer Protocol (FTP), Apple File Service (AFS), Wireless Application Protocol (WAP), etc. In an example where HTTP is used, each user system 12 can include an HTTP client commonly referred to as a “web browser” or simply a “browser” for sending and receiving HTTP signals to and from an HTTP server of the database system 16. Such an HTTP server can be implemented as the sole network interface 20 between the database system 16 and the network 14, but other techniques can be used in addition to or instead of these techniques. In some implementations, the network interface 20 between the database system 16 and the network 14 includes load sharing functionality, such as round-robin HTTP request distributors to balance loads and distribute incoming HTTP requests evenly over a number of servers. In MTS implementations, each of the servers can have access to the MTS data; however, other alternative configurations may be used instead.

The user systems 12 can be implemented as any computing device(s) or other data processing apparatus or systems usable by users to access the database system 16. For example, any of user systems 12 can be a desktop computer, a work station, a laptop computer, a tablet computer, a handheld computing device, a mobile cellular phone (for example, a “smartphone”), or any other Wi-Fi-enabled device, WAP-enabled device, or other computing device capable of interfacing directly or indirectly to the Internet or other network. When discussed in the context of a user, the terms “user system,” “user device,” and “user computing device” are used interchangeably herein with one another and with the term “computer.” As described above, each user system 12 typically executes an HTTP client, for example, a web browsing (or simply “browsing”) program, such as a web browser based on the WebKit platform, Microsoft's Internet Explorer browser, Netscape's Navigator browser, Opera's browser, Mozilla's Firefox browser, or a WAP-enabled browser in the case of a cellular phone, personal digital assistant (PDA), or other wireless device, allowing a user (for example, a subscriber of on-demand services provided by the database system 16) of the user system 12 to access, process, and view information, pages, and applications available to it from the database system 16 over the network 14.

Each user system 12 also typically includes one or more user input devices, such as a keyboard, a mouse, a trackball, a touch pad, a touch screen, a pen or stylus, or the like, for interacting with a graphical user interface (GUI) provided by the browser on a display (for example, a monitor screen, liquid crystal display (LCD), light-emitting diode (LED) display, etc.) of the user system 12 in conjunction with pages, forms, applications, and other information provided by the database system 16 or other systems or servers. For example, the user interface device can be used to access data and applications hosted by database system 16, and to perform searches on stored data, or otherwise allow a user to interact with various GUI pages that may be presented to a user. As discussed above, implementations are suitable for use with the Internet, although other networks can be used instead of or in addition to the Internet, such as an intranet, an extranet, a virtual private network (VPN), a non-TCP/IP based network, any LAN or WAN or the like.

The users of user systems 12 may differ in their respective capacities, and the capacity of a particular user system 12 can be entirely determined by permissions (permission levels) for the current user of such user system. For example, where a salesperson is using a particular user system 12 to interact with the database system 16, that user system can have the capacities allotted to the salesperson. However, while an administrator is using that user system 12 to interact with the database system 16, that user system can have the capacities allotted to that administrator. Where a hierarchical role model is used, users at one permission level can have access to applications, data, and database information accessible by a lower permission level user, but may not have access to certain applications, database information, and data accessible by a user at a higher permission level. Thus, different users generally will have different capabilities with regard to accessing and modifying application and database information, depending on the users' respective security or permission levels (also referred to as “authorizations”).

According to some implementations, each user system 12 and some or all of its components are operator-configurable using applications, such as a browser, including computer code executed using a central processing unit (CPU), such as an Intel Pentium® processor or the like. Similarly, the database system 16 (and additional instances of an MTS, where more than one is present) and all of its components can be operator-configurable using application(s) including computer code to run using the processor system 17, which may be implemented to include a CPU, which may include an Intel Pentium® processor or the like, or multiple CPUs.

The database system 16 includes non-transitory computer-readable storage media having instructions stored thereon that are executable by or used to program a server or other computing system (or collection of such servers or computing systems) to perform some of the implementation of processes described herein. For example, the program code 26 can include instructions for operating and configuring the database system 16 to intercommunicate and to process web pages, applications, and other data and media content as described herein. In some implementations, the program code 26 can be downloadable and stored on a hard disk, but the entire program code, or portions thereof, also can be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, DVDs, CDs, microdrives, magneto-optical discs, magnetic or optical cards, nanosystems (including molecular memory integrated circuits), or any other type of computer-readable medium or device suitable for storing instructions or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, for example, over the Internet, or from another server, as is well known, or transmitted over any other existing network connection as is well known (for example, extranet, VPN, LAN, etc.) using any communication medium and protocols (for example, TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for the disclosed implementations can be realized in any programming language that can be executed on a server or other computing system such as, for example, C, C++, HTML, any other markup language, Java™, JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known.

FIG. 1B shows a block diagram of example implementations of elements of FIG. 1A and example interconnections between these elements according to some implementations. That is, FIG. 1B also illustrates environment 10, but FIG. 1B, various elements of the database system 16 and various interconnections between such elements are shown with more specificity according to some more specific implementations. In some implementations, the database system 16 may not have the same elements as those described herein or may have other elements instead of, or in addition to, those described herein.

In FIG. 1B, the user system 12 includes a processor system 12A, a memory system 12B, an input system 12C, and an output system 12D. The processor system 12A can include any suitable combination of one or more processors. The memory system 12B can include any suitable combination of one or more memory devices. The input system 12C can include any suitable combination of input devices, such as one or more touchscreen interfaces, keyboards, mice, trackballs, scanners, cameras, or interfaces to networks. The output system 12D can include any suitable combination of output devices, such as one or more display devices, printers, or interfaces to networks.

In FIG. 1B, the network interface 20 is implemented as a set of HTTP application servers 100 ₁-100 _(N). Each application server 100, also referred to herein as an “app server,” is configured to communicate with tenant database 22 and the tenant data 23 therein, as well as system database 24 and the system data 25 therein, to serve requests received from the user systems 12. The tenant data 23 can be divided into individual tenant storage spaces 112, which can be physically or logically arranged or divided. Within each tenant storage space 112, user storage 114, and application metadata 116 can similarly be allocated for each user. For example, a copy of a user's most recently used (MRU) items can be stored to user storage 114. Similarly, a copy of MRU items for an entire organization that is a tenant can be stored to tenant storage space 112.

The database system 16 of FIG. 1B also includes a user interface (UI) 30 and an application programming interface (API) 32. The process space 28 includes system process space 102, individual tenant process spaces 104 and a tenant management process space 110. The application platform 18 includes an application setup mechanism 38 that supports application developers' creation and management of applications. Such applications and others can be saved as metadata into tenant database 22 by save routines 36 for execution by subscribers as one or more tenant process spaces 104 managed by tenant management process space 110, for example. Invocations to such applications can be coded using PL/SOQL 34, which provides a programming language style interface extension to the API 32. A detailed description of some PL/SOQL language implementations is discussed in commonly assigned U.S. Pat. No. 7,730,478, titled METHOD AND SYSTEM FOR ALLOWING ACCESS TO DEVELOPED APPLICATIONS VIA A MULTI-TENANT ON-DEMAND DATABASE SERVICE, issued on Jun. 1, 2010, and hereby incorporated by reference herein in its entirety and for all purposes. Invocations to applications can be detected by one or more system processes, which manage retrieving application metadata 116 for the subscriber making the invocation and executing the metadata as an application in a virtual machine.

Each application server 100 can be communicably coupled with tenant database 22 and system database 24, for example, having access to tenant data 23 and system data 25, respectively, via a different network connection. For example, one application server 100 ₁ can be coupled via the network 14 (for example, the Internet), another application server 100 ₂ can be coupled via a direct network link, and another application server 100 _(N) can be coupled by yet a different network connection. Transfer Control Protocol and Internet Protocol (TCP/IP) are examples of typical protocols that can be used for communicating between application servers 100 and the database system 16. However, it will be apparent to one skilled in the art that other transport protocols can be used to optimize the database system 16 depending on the network interconnections used.

In some implementations, each application server 100 is configured to handle requests for any user associated with any organization that is a tenant of the database system 16. Because it can be desirable to be able to add and remove application servers 100 from the server pool at any time and for various reasons, in some implementations there is no server affinity for a user or organization to a specific application server 100. In some such implementations, an interface system implementing a load balancing function (for example, an F5 Big-IP load balancer) is communicably coupled between the application servers 100 and the user systems 12 to distribute requests to the application servers 100. In one implementation, the load balancer uses a least-connections algorithm to route user requests to the application servers 100. Other examples of load balancing algorithms, such as round robin and observed-response-time, also can be used. For example, in some instances, three consecutive requests from the same user could hit three different application servers 100, and three requests from different users could hit the same application server 100. In this manner, by way of example, database system 16 can be a multi-tenant system in which database system 16 handles storage of, and access to, different objects, data, and applications across disparate users and organizations.

In one example storage use case, one tenant can be a company that employs a sales force where each salesperson uses database system 16 to manage aspects of their sales. A user can maintain contact data, leads data, customer follow-up data, performance data, goals and progress data, etc., all applicable to that user's personal sales process (for example, in tenant database 22). In an example of a MTS arrangement, because all of the data and the applications to access, view, modify, report, transmit, calculate, etc., can be maintained and accessed by a user system 12 having little more than network access, the user can manage his or her sales efforts and cycles from any of many different user systems. For example, when a salesperson is visiting a customer and the customer has Internet access in their lobby, the salesperson can obtain critical updates regarding that customer while waiting for the customer to arrive in the lobby.

While each user's data can be stored separately from other users' data regardless of the employers of each user, some data can be organization-wide data shared or accessible by several users or all of the users for a given organization that is a tenant. Thus, there can be some data structures managed by database system 16 that are allocated at the tenant level while other data structures can be managed at the user level. Because an MTS can support multiple tenants including possible competitors, the MTS can have security protocols that keep data, applications, and application use separate. Also, because many tenants may opt for access to an MTS rather than maintain their own system, redundancy, up-time, and backup are additional functions that can be implemented in the MTS. In addition to user-specific data and tenant-specific data, the database system 16 also can maintain system level data usable by multiple tenants or other data. Such system level data can include industry reports, news, postings, and the like that are sharable among tenants.

In some implementations, the user systems 12 (which also can be client systems) communicate with the application servers 100 to request and update system-level and tenant-level data from the database system 16. Such requests and updates can involve sending one or more queries to tenant database 22 or system database 24. The database system 16 (for example, an application server 100 in the database system 16) can automatically generate one or more structure query language (SQL) statements (for example, one or more SQL queries) designed to access the desired information. System database 24 can generate query plans to access the requested data from the database. The term “query plan” generally refers to one or more operations used to access information in a database system.

Each database can generally be viewed as a collection of objects, such as a set of logical tables, containing data fitted into predefined or customizable categories. A “table” is one representation of a data object, and may be used herein to simplify the conceptual description of objects and custom objects according to some implementations. It should be understood that “table” and “object” may be used interchangeably herein. Each table generally contains one or more data categories logically arranged as columns or fields in a viewable schema. Each row or element of a table can contain an instance of data for each category defined by the fields. For example, a CRM database can include a table that describes a customer with fields for basic contact information such as name, address, phone number, fax number, etc. Another table can describe a purchase order, including fields for information such as customer, product, sale price, date, etc. In some MTS implementations, standard entity tables can be provided for use by all tenants. For CRM database applications, such standard entities can include tables for case, account, contact, lead, and opportunity data objects, each containing pre-defined fields. As used herein, the term “entity” also may be used interchangeably with “object” and “table.”

In some MTS implementations, tenants are allowed to create and store custom objects, or may be allowed to customize standard entities or objects, for example by creating custom fields for standard objects, including custom index fields. Commonly assigned U.S. Pat. No. 7,779,039, titled CUSTOM ENTITIES AND FIELDS IN A MULTI-TENANT DATABASE SYSTEM, issued on Aug. 17, 2010, and hereby incorporated by reference herein in its entirety and for all purposes, teaches systems and methods for creating custom objects as well as customizing standard objects in a multi-tenant database system. In some implementations, for example, all custom entity data rows are stored in a single multi-tenant physical table, which may contain multiple logical tables per organization. It is transparent to customers that their multiple “tables” are in fact stored in one large table or that their data may be stored in the same table as the data of other customers.

FIG. 2A shows a system diagram illustrating example architectural components of an on-demand database service environment 200 according to some implementations. A client machine communicably connected with the cloud 204, generally referring to one or more networks in combination, as described herein, can communicate with the on-demand database service environment 200 via one or more edge routers 208 and 212. A client machine can be any of the examples of user systems 12 described above. The edge routers can communicate with one or more core switches 220 and 224 through a firewall 216. The core switches can communicate with a load balancer 228, which can distribute server load over different pods, such as the pods 240 and 244. The pods 240 and 244, which can each include one or more servers or other computing resources, can perform data processing and other operations used to provide on-demand services. Communication with the pods can be conducted via pod switches 232 and 236. Components of the on-demand database service environment can communicate with database storage 256 through a database firewall 248 and a database switch 252.

As shown in FIGS. 2A and 2B, accessing an on-demand database service environment can involve communications transmitted among a variety of different hardware or software components. Further, the on-demand database service environment 200 is a simplified representation of an actual on-demand database service environment. For example, while only one or two devices of each type are shown in FIGS. 2A and 2B, some implementations of an on-demand database service environment can include anywhere from one to several devices of each type. Also, the on-demand database service environment need not include each device shown in FIGS. 2A and 2B, or can include additional devices not shown in FIGS. 2A and 2B.

Additionally, it should be appreciated that one or more of the devices in the on-demand database service environment 200 can be implemented on the same physical device or on different hardware. Some devices can be implemented using hardware or a combination of hardware and software. Thus, terms such as “data processing apparatus,” “machine,” “server,” “device,” and “processing device” as used herein are not limited to a single hardware device; rather, references to these terms can include any suitable combination of hardware and software configured to provide the described functionality.

The cloud 204 is intended to refer to a data network or multiple data networks, often including the Internet. Client machines communicably connected with the cloud 204 can communicate with other components of the on-demand database service environment 200 to access services provided by the on-demand database service environment. For example, client machines can access the on-demand database service environment to retrieve, store, edit, or process information. In some implementations, the edge routers 208 and 212 route packets between the cloud 204 and other components of the on-demand database service environment 200. For example, the edge routers 208 and 212 can employ the Border Gateway Protocol (BGP). The BGP is the core routing protocol of the Internet. The edge routers 208 and 212 can maintain a table of Internet Protocol (IP) networks or ‘prefixes,’ which designate network reachability among autonomous systems on the Internet.

In some implementations, the firewall 216 can protect the inner components of the on-demand database service environment 200 from Internet traffic. The firewall 216 can block, permit, or deny access to the inner components of the on-demand database service environment 200 based upon a set of rules and other criteria. The firewall 216 can act as one or more of a packet filter, an application gateway, a stateful filter, a proxy server, or any other type of firewall.

In some implementations, the core switches 220 and 224 are high-capacity switches that transfer packets within the on-demand database service environment 200. The core switches 220 and 224 can be configured as network bridges that quickly route data between different components within the on-demand database service environment. In some implementations, the use of two or more core switches 220 and 224 can provide redundancy or reduced latency.

In some implementations, the pods 240 and 244 perform the core data processing and service functions provided by the on-demand database service environment. Each pod can include various types of hardware or software computing resources. An example of the pod architecture is discussed in greater detail with reference to FIG. 2B. In some implementations, communication between the pods 240 and 244 is conducted via the pod switches 232 and 236. The pod switches 232 and 236 can facilitate communication between the pods 240 and 244 and client machines communicably connected with the cloud 204, for example, via core switches 220 and 224. Also, the pod switches 232 and 236 may facilitate communication between the pods 240 and 244 and the database storage 256. In some implementations, the load balancer 228 can distribute workload between the pods 240 and 244. Balancing the on-demand service requests between the pods can assist in improving the use of resources, increasing throughput, reducing response times, or reducing overhead. The load balancer 228 may include multilayer switches to analyze and forward traffic.

In some implementations, access to the database storage 256 is guarded by a database firewall 248. The database firewall 248 can act as a computer application firewall operating at the database application layer of a protocol stack. The database firewall 248 can protect the database storage 256 from application attacks such as SQL injection, database rootkits, and unauthorized information disclosure. In some implementations, the database firewall 248 includes a host using one or more forms of reverse proxy services to proxy traffic before passing it to a gateway router. The database firewall 248 can inspect the contents of database traffic and block certain content or database requests. The database firewall 248 can work on the SQL application level atop the TCP/IP stack, managing applications' connection to the database or SQL management interfaces as well as intercepting and enforcing packets traveling to or from a database network or application interface.

In some implementations, communication with the database storage 256 is conducted via the database switch 252. The multi-tenant database storage 256 can include more than one hardware or software components for handling database queries. Accordingly, the database switch 252 can direct database queries transmitted by other components of the on-demand database service environment (for example, the pods 240 and 244) to the correct components within the database storage 256. In some implementations, the database storage 256 is an on-demand database system shared by many different organizations as described above with reference to FIGS. 1A and 1B.

FIG. 2B shows a system diagram further illustrating example architectural components of an on-demand database service environment according to some implementations. The pod 244 can be used to render services to a user of the on-demand database service environment 200. In some implementations, each pod includes a variety of servers or other systems. The pod 244 includes one or more content batch servers 264, content search servers 268, query servers 282, file servers 286, access control system (ACS) servers 280, batch servers 284, and app servers 288. The pod 244 also can include database instances 290, quick file systems (QFS) 292, and indexers 294. In some implementations, some or all communication between the servers in the pod 244 can be transmitted via the pod switch 236.

In some implementations, the app servers 288 include a hardware or software framework dedicated to the execution of procedures (for example, programs, routines, scripts) for supporting the construction of applications provided by the on-demand database service environment 200 via the pod 244. In some implementations, the hardware or software framework of an app server 288 is configured to execute operations of the services described herein, including performance of the blocks of various methods or processes described herein. In some alternative implementations, two or more app servers 288 can be included and cooperate to perform such methods, or one or more other servers described herein can be configured to perform the disclosed methods.

The content batch servers 264 can handle requests internal to the pod. Some such requests can be long-running or not tied to a particular customer. For example, the content batch servers 264 can handle requests related to log mining, cleanup work, and maintenance tasks. The content search servers 268 can provide query and indexer functions. For example, the functions provided by the content search servers 268 can allow users to search through content stored in the on-demand database service environment. The file servers 286 can manage requests for information stored in the file storage 298. The file storage 298 can store information such as documents, images, and binary large objects (BLOBs). By managing requests for information using the file servers 286, the image footprint on the database can be reduced. The query servers 282 can be used to retrieve information from one or more file systems. For example, the query servers 282 can receive requests for information from the app servers 288 and transmit information queries to the network file systems (NFS) 296 located outside the pod.

The pod 244 can share a database instance 290 configured as a multi-tenant environment in which different organizations share access to the same database. Additionally, services rendered by the pod 244 may call upon various hardware or software resources. In some implementations, the ACS servers 280 control access to data, hardware resources, or software resources. In some implementations, the batch servers 284 process batch jobs, which are used to run tasks at specified times. For example, the batch servers 284 can transmit instructions to other servers, such as the app servers 288, to trigger the batch jobs.

In some implementations, the QFS 292 is an open source file system available from Sun Microsystems, Inc. The QFS can serve as a rapid-access file system for storing and accessing information available within the pod 244. The QFS 292 can support some volume management capabilities, allowing many disks to be grouped together into a file system. File system metadata can be kept on a separate set of disks, which can be useful for streaming applications where long disk seeks cannot be tolerated. Thus, the QFS system can communicate with one or more content search servers 268 or indexers 294 to identify, retrieve, move, or update data stored in the NFS 296 or other storage systems.

In some implementations, one or more query servers 282 communicate with the NFS 296 to retrieve or update information stored outside of the pod 244. The NFS 296 can allow servers located in the pod 244 to access information to access files over a network in a manner similar to how local storage is accessed. In some implementations, queries from the query servers 282 are transmitted to the NFS 296 via the load balancer 228, which can distribute resource requests over various resources available in the on-demand database service environment. The NFS 296 also can communicate with the QFS 292 to update the information stored on the NFS 296 or to provide information to the QFS 292 for use by servers located within the pod 244.

In some implementations, the pod includes one or more database instances 290. The database instance 290 can transmit information to the QFS 292. When information is transmitted to the QFS, it can be available for use by servers within the pod 244 without using an additional database call. In some implementations, database information is transmitted to the indexer 294. Indexer 294 can provide an index of information available in the database instance 290 or QFS 292. The index information can be provided to the file servers 286 or the QFS 292.

FIG. 3 illustrates a diagrammatic representation of a machine in the exemplary form of a computer system 300 within which a set of instructions (e.g., for causing the machine to perform any one or more of the methodologies discussed herein) may be executed. In alternative implementations, the machine may be connected (e.g., networked) to other machines in a LAN, a WAN, an intranet, an extranet, or the Internet. The machine may operate in the capacity of a server or a client machine in client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a PDA, a cellular telephone, a web appliance, a server, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. Some or all of the components of the computer system 300 may be utilized by or illustrative of any of the electronic components described herein (e.g., any of the components illustrated in or described with respect to FIGS. 1A, 1B, 2A, and 2B).

The exemplary computer system 300 includes a processing device (processor) 302, a main memory 304 (e.g., ROM, flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM), etc.), a static memory 306 (e.g., flash memory, static random access memory (SRAM), etc.), and a data storage device 320, which communicate with each other via a bus 310.

Processor 302 represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. More particularly, the processor 302 may be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets. The processor 302 may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. The processor 302 is configured to execute instructions 326 for performing the operations and steps discussed herein.

The computer system 300 may further include a network interface device 308. The computer system 300 also may include a video display unit 312 (e.g., a liquid crystal display (LCD), a cathode ray tube (CRT), or a touch screen), an alphanumeric input device 314 (e.g., a keyboard), a cursor control device 316 (e.g., a mouse), and a signal generation device 322 (e.g., a speaker).

Power device 318 may monitor a power level of a battery used to power the computer system 300 or one or more of its components. The power device 718 may provide one or more interfaces to provide an indication of a power level, a time window remaining prior to shutdown of computer system 300 or one or more of its components, a power consumption rate, an indicator of whether computer system is utilizing an external power source or battery power, and other power related information. In some implementations, indications related to the power device 318 may be accessible remotely (e.g., accessible to a remote back-up management module via a network connection). In some implementations, a battery utilized by the power device 318 may be an uninterruptable power supply (UPS) local to or remote from computer system 300. In such implementations, the power device 318 may provide information about a power level of the UPS.

The data storage device 320 may include a computer-readable storage medium 324 (e.g., a non-transitory computer-readable storage medium) on which is stored one or more sets of instructions 326 (e.g., software) embodying any one or more of the methodologies or functions described herein. The instructions 326 may also reside, completely or at least partially, within the main memory 304 and/or within the processor 302 during execution thereof by the computer system 300, the main memory 304, and the processor 302 also constituting computer-readable storage media. The instructions 326 may further be transmitted or received over a network 330 (e.g., the network 14) via the network interface device 308.

In one implementation, the instructions 326 include instructions for performing any of the implementations described herein. While the computer-readable storage medium 324 is shown in an exemplary implementation to be a single medium, it is to be understood that the computer-readable storage medium 324 may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions.

II. Enterprise Social Networking

As initially described above, in some implementations, some of the methods, processes, devices, and systems described herein can implement, or be used in the context of, enterprise social networking. An “enterprise” refers generally to a company or organization that owns one or more data centers that host various services and data sources. A “data center” refers generally to a physical location of various servers, machines, and network components utilized by an enterprise. Some online enterprise social networks can be implemented in various settings, including businesses, organizations, and other enterprises (all of which are used interchangeably herein). For instance, an online enterprise social network can be implemented to connect users within a business corporation, partnership, or organization, or a group of users within such an enterprise. For instance, Chatter® can be used by users who are employees in a business organization to share data, communicate, and collaborate with each other for various enterprise-related purposes. Some of the disclosed methods, processes, devices, systems, and computer-readable storage media described herein can be configured or designed for use in a multi-tenant database environment, such as described above with respect to the database system 16. In an example implementation, each organization or a group within the organization can be a respective tenant of the system.

In some implementations, each user of the database system 16 is associated with a “user profile.” A user profile refers generally to a collection of data about a given user. The data can include general information, such as a name, a title, a phone number, a photo, a biographical summary, or a status (for example, text describing what the user is currently doing, thinking, or expressing). As described below, the data can include messages created by other users. In implementations in which there are multiple tenants, a user is typically associated with a particular tenant (or “organization”). For example, a user could be a salesperson of an organization that is a tenant of the database system 16. As used herein, a “customer” may be an individual or organization that receives emails or other data and communications from a user. A customer may also be a user in certain scenarios.

A “group” generally refers to a collection of users within an organization. In some implementations, a group can be defined as users with one or more same or a similar attributes, or by membership or subscription. Groups can have various visibilities to users within an enterprise social network. For example, some groups can be private while others can be public. In some implementations, to become a member within a private group, and to have the capability to publish and view feed items on the group's group feed, a user must request to be subscribed to the group (and be accepted by, for example, an administrator or owner of the group), be invited to subscribe to the group (and accept), or be directly subscribed to the group (for example, by an administrator or owner of the group). In some implementations, any user within the enterprise social network can subscribe to or follow a public group (and thus become a “member” of the public group) within the enterprise social network.

A “record” generally refers to a data entity, such as an instance of a data object created by a user or group of users of the database system 16. Such records can include, for example, data objects representing and maintaining data for accounts, cases, opportunities, leads, files, documents, orders, pricebooks, products, solutions, reports, and forecasts, among other possibilities. For example, a record can be for a partner or potential partner (for example, a client, vendor, distributor, etc.) of a user or a user's organization, and can include information describing an entire enterprise, subsidiaries of an enterprise, or contacts at the enterprise. As another example, a record can be a project that a user or group of users is/are working on, such as an opportunity with an existing partner, or a project that the user is trying to obtain. A record has data fields that are defined by the structure of the object (for example, fields of certain data types and purposes). A record also can have custom fields defined by a user or organization. A field can include (or include a link to) another record, thereby providing a parent-child relationship between the records.

Records also can have various visibilities to users within an enterprise social network. For example, some records can be private while others can be public. In some implementations, to access a private record, and to have the capability to publish and view feed items on the record's record feed, a user must request to be subscribed to the record (and be accepted by, for example, an administrator or owner of the record), be invited to subscribe to the record (and accept), be directly subscribed to the record or be shared the record (for example, by an administrator or owner of the record). In some implementations, any user within the enterprise social network can subscribe to or follow a public record within the enterprise social network.

In some online enterprise social networks, users also can follow one another by establishing “links” or “connections” with each other, sometimes referred to as “friending” one another. By establishing such a link, one user can see information generated by, generated about, or otherwise associated with another user. For instance, a first user can see information posted by a second user to the second user's profile page. In one example, when the first user is following the second user, the first user's news feed can receive a post from the second user submitted to the second user's profile feed.

In some implementations, users can access one or more enterprise network feeds (also referred to herein simply as “feeds”), which include publications presented as feed items or entries in the feed. A network feed can be displayed in a graphical user interface (GUI) on a display device such as the display of a user's computing device as described above. The publications can include various enterprise social network information or data from various sources and can be stored in the database system 16, for example, in tenant database 22. In some implementations, feed items of information for or about a user can be presented in a respective user feed, feed items of information for or about a group can be presented in a respective group feed, and feed items of information for or about a record can be presented in a respective record feed. A second user following a first user, a first group, or a first record can automatically receive the feed items associated with the first user, the first group, or the first record for display in the second user's news feed. In some implementations, a user feed also can display feed items from the group feeds of the groups the respective user subscribes to, as well as feed items from the record feeds of the records the respective user subscribes to.

The term “feed item” (or feed element) refers to an item of information, which can be viewable in a feed. Feed items can include publications such as messages (for example, user-generated textual posts or comments), files (for example, documents, audio data, image data, video data or other data), and “feed-tracked” updates associated with a user, a group, or a record (feed-tracked updates are described in greater detail below). A feed item, and a feed in general, can include combinations of messages, files, and feed-tracked updates. Documents and other files can be included in, linked with, or attached to a post or comment. For example, a post can include textual statements in combination with a document. The feed items can be organized in chronological order or another suitable or desirable order (which can be customizable by a user) when the associated feed is displayed in a graphical user interface (GUI), for instance, on the user's computing device.

Messages such as posts can include alpha-numeric or other character-based user inputs such as words, phrases, statements, questions, emotional expressions, or symbols. In some implementations, a comment can be made on any feed item. In some implementations, comments are organized as a list explicitly tied to a particular feed item such as a feed-tracked update, post, or status update. In some implementations, comments may not be listed in the first layer (in a hierarchal sense) of feed items, but listed as a second layer branching from a particular first layer feed item. In some implementations, a “like” or “dislike” also can be submitted in response to a particular post, comment, or other publication.

A “feed-tracked update,” also referred to herein as a “feed update,” is another type of publication that may be presented as a feed item and generally refers to data representing an event. A feed-tracked update can include text generated by the database system in response to the event, to be provided as one or more feed items for possible inclusion in one or more feeds. In one implementation, the data can initially be stored by the database system in, for example, tenant database 22, and subsequently used by the database system to create text for describing the event. Both the data and the text can be a feed-tracked update, as used herein. In some implementations, an event can be an update of a record and can be triggered by a specific action by a user. Which actions trigger an event can be configurable. Which events have feed-tracked updates created and which feed updates are sent to which users also can be configurable. Messages and feed updates can be stored as a field or child object of a record. For example, the feed can be stored as a child object of the record.

As described above, a network feed can be specific to an individual user of an online social network. For instance, a user news feed (or “user feed”) generally refers to an aggregation of feed items generated for a particular user, and in some implementations, is viewable only to the respective user on a home page of the user. In some implementations a user profile feed (also referred to as a “user feed”) is another type of user feed that refers to an aggregation of feed items generated by or for a particular user, and in some implementations, is viewable only by the respective user and other users following the user on a profile page of the user. As a more specific example, the feed items in a user profile feed can include posts and comments that other users make about or send to the particular user, and status updates made by the particular user. As another example, the feed items in a user profile feed can include posts made by the particular user and feed-tracked updates initiated based on actions of the particular user.

As is also described above, a network feed can be specific to a group of enterprise users of an online enterprise social network. For instance, a group news feed (or “group feed”) generally refers to an aggregation of feed items generated for or about a particular group of users of the database system 16 and can be viewable by users following or subscribed to the group on a profile page of the group. For example, such feed items can include posts made by members of the group or feed-tracked updates about changes to the respective group (or changes to documents or other files shared with the group). Members of the group can view and post to a group feed in accordance with a permissions configuration for the feed and the group. Publications in a group context can include documents, posts, or comments. In some implementations, the group feed also includes publications and other feed items that are about the group as a whole, the group's purpose, the group's description, a status of the group, and group records and other objects stored in association with the group. Threads of publications including updates and messages, such as posts, comments, likes, etc., can define conversations and change over time. The following of a group allows a user to collaborate with other users in the group, for example, on a record or on documents or other files (which may be associated with a record).

As is also described above, a network feed can be specific to a record in an online enterprise social network. For instance, a record news feed (or “record feed”) generally refers to an aggregation of feed items about a particular record in the database system 16 and can be viewable by users subscribed to the record on a profile page of the record. For example, such feed items can include posts made by users about the record or feed-tracked updates about changes to the respective record (or changes to documents or other files associated with the record). Subscribers to the record can view and post to a record feed in accordance with a permissions configuration for the feed and the record. Publications in a record context also can include documents, posts, or comments. In some implementations, the record feed also includes publications and other feed items that are about the record as a whole, the record's purpose, the record's description, and other records or other objects stored in association with the record. Threads of publications including updates and messages, such as posts, comments, likes, etc., can define conversations and change over time. The following of a record allows a user to track the progress of that record and collaborate with other users subscribing to the record, for example, on the record or on documents or other files associated with the record.

In some implementations, data is stored in the database system 16, including tenant database 22, in the form of “entity objects” (also referred to herein simply as “entities”). In some implementations, entities are categorized into “Records objects” and “Collaboration objects.” In some such implementations, the Records object includes all records in the enterprise social network. Each record can be considered a sub-object of the overarching Records object. In some implementations, Collaboration objects include, for example, a “Users object,” a “Groups object,” a “Group-User relationship object,” a “Record-User relationship object,” and a “Feed Items object.”

In some implementations, the Users object is a data structure that can be represented or conceptualized as a “Users Table” that associates users to information about or pertaining to the respective users including, for example, metadata about the users. In some implementations, the Users Table includes all of the users within an organization. In some other implementations, there can be a Users Table for each division, department, team or other sub-organization within an organization. In implementations in which the organization is a tenant of a multi-tenant enterprise social network platform, the Users Table can include all of the users within all of the organizations that are tenants of the multi-tenant enterprise social network platform. In some implementations, each user can be identified by a user identifier (“UserID”) that is unique at least within the user's respective organization. In some such implementations, each organization also has a unique organization identifier (“OrgID”).

In some implementations, the Groups object is a data structure that can be represented or conceptualized as a “Groups Table” that associates groups to information about or pertaining to the respective groups including, for example, metadata about the groups. In some implementations, the Groups Table includes all of the groups within the organization. In some other implementations, there can be a Groups Table for each division, department, team, or other sub-organization within an organization. In implementations in which the organization is a tenant of a multi-tenant enterprise social network platform, the Groups Table can include all of the groups within all of the organizations that are tenants of the multitenant enterprise social network platform. In some implementations, each group can be identified by a group identifier (“GroupID”) that is unique at least within the respective organization.

In some implementations, the database system 16 includes a “Group-User relationship object.” The Group-User relationship object is a data structure that can be represented or conceptualized as a “Group-User Table” that associates groups to users subscribed to the respective groups. In some implementations, the Group-User Table includes all of the groups within the organization. In some other implementations, there can be a Group-User Table for each division, department, team, or other sub-organization within an organization. In implementations in which the organization is a tenant of a multi-tenant enterprise social network platform, the Group-User Table can include all of the groups within all of the organizations that are tenants of the multitenant enterprise social network platform.

In some implementations, the Records object is a data structure that can be represented or conceptualized as a “Records Table” that associates records to information about or pertaining to the respective records including, for example, metadata about the records. In some implementations, the Records Table includes all of the records within the organization. In some other implementations, there can be a Records Table for each division, department, team, or other sub-organization within an organization. In implementations in which the organization is a tenant of a multi-tenant enterprise social network platform, the Records Table can include all of the records within all of the organizations that are tenants of the multitenant enterprise social network platform. In some implementations, each record can be identified by a record identifier (“RecordID”) that is unique at least within the respective organization.

In some implementations, the database system 16 includes a “Record-User relationship object.” The Record-User relationship object is a data structure that can be represented or conceptualized as a “Record-User Table” that associates records to users subscribed to the respective records. In some implementations, the Record-User Table includes all of the records within the organization. In some other implementations, there can be a Record-User Table for each division, department, team, or other sub-organization within an organization. In implementations in which the organization is a tenant of a multi-tenant enterprise social network platform, the Record-User Table can include all of the records within all of the organizations that are tenants of the multitenant enterprise social network platform.

In some implementations, the database system 16 includes a “Feed Items object.” The Feed Items object is a data structure that can be represented or conceptualized as a “Feed Items Table” that associates users, records, and groups to posts, comments, documents, or other publications to be displayed as feed items in the respective user feeds, record feeds, and group feeds, respectively. In some implementations, the Feed Items Table includes all of the feed items within the organization. In some other implementations, there can be a Feed Items Table for each division, department, team, or other sub-organization within an organization. In implementations in which the organization is a tenant of a multi-tenant enterprise social network platform, the Feed Items Table can include all of the feed items within all of the organizations that are tenants of the multitenant enterprise social network platform.

Enterprise social network news feeds are different from typical consumer-facing social network news feeds (for example, FACEBOOK®) in many ways, including in the way they prioritize information. In consumer-facing social networks, the focus is generally on helping the social network users find information that they are personally interested in. But in enterprise social networks, it can, in some instances, applications, or implementations, be desirable from an enterprise's perspective to only distribute relevant enterprise-related information to users and to limit the distribution of irrelevant information. In some implementations, relevant enterprise-related information refers to information that would be predicted or expected to benefit the enterprise by virtue of the recipients knowing the information, such as an update to a database record maintained by or on behalf of the enterprise. Thus, the meaning of relevance differs significantly in the context of a consumer-facing social network as compared with an employee-facing or organization member-facing enterprise social network.

In some implementations, when data such as posts or comments from one or more enterprise users are submitted to a network feed for a particular user, group, record or other object within an online enterprise social network, an email notification, or other type of network communication may be transmitted to all users following the respective user, group, record, or object in addition to the inclusion of the data as a feed item in one or more user, group, record, or other feeds. In some online enterprise social networks, the occurrence of such a notification is limited to the first instance of a published input, which may form part of a larger conversation. For instance, a notification may be transmitted for an initial post, but not for comments on the post. In some other implementations, a separate notification is transmitted for each such publication, such as a comment on a post.

III. Data Resolution

Certain implementations relate to a system and method for management and movement of data which may be achieved by introducing a data resolution layer that orchestrates data movement and centralizes schema registration. The management and movement of data may be transparent to the user. A common problem in data management systems is that end users must know the location of remote data in order to request or import it. Human consumers of this data may know the name of the system from which they want to query data and/or the path, but not the actual endpoint in an enterprise system. In practice, users of software as a service (SaaS) products typically require data that resides in three or more different data centers.

In certain implementations, the data resolution functionality is performed in a SaaS environment. In other implementations, the data resolution functionality is implemented as part of an on an on-premise solution. In certain implementations, the data resolution functionality is agnostic to open source technologies which may be used to implement other functionalities (e.g., ZooKeeper for configuration information, naming, providing distributed synchronization, and providing group services). In certain implementations, the data resolution functionality is agnostic to compression algorithms implemented. In certain implementations, the data resolution functionality is agnostic to the securing of HTTP and TCP transport and endpoints. In certain implementations, node-to-node communication may be asynchronous.

FIG. 4 is a system topology 400 diagram illustrating the interplay between various systems according to some implementations. The functionality of the system topology 400 may be implemented, for example, by one or more of the components of the environment 10. The system topology 400 includes a target system 410 that is communicatively coupled to data sources 420, 430, and 430 via a network (e.g., the network 14). The target system 410 may host various nodes, such as data consumer nodes 412 and 414, a data resolution node 416, and a schema node 418. The target system 410 may host one or more additional data resolution nodes or schema nodes. In certain implementations, the target system 410 may further host one or more data source nodes, which may be similar to the data source nodes of data sources 420, 430, and 440. In some implementations, some or all of the functionality of the target system 410 may be performed by one or more servers, such as one or more of the application servers 100 ₁-100 _(N) described with respect to FIG. 1B. For example, one or more data resolutions servers may host the data resolution node 416 and the schema node 418, and implement the functionality of these nodes by processing devices.

In certain implementations, data resolution requests may be generated at the data consumer nodes 412 and 414. For example, a data consumer utilizing an application that requires data from one or more of data sources 420, 430, and 440 may generate a data resolution request that is to be resolved by the data resolution node 416. In certain implementations, the data resolution request comprises a data object having data fields that contain data expressions to indicate the data desired. The data consumer may allow for the selection of particular names of data (e.g., “Customer Name,” “Customer Address,” etc.) that map to predicates which are built into the data resolution request at a data consumer node. In certain implementations, the data consumer nodes 412 and 414 may store resolved data objects until requested by the application or applications that generated the data resolution requests.

In certain implementations, the data resolution node 416 receives data resolution requests from one or more of the user nodes 412 or 414, and then identifies, based on a master schema, data sources that store some or all of the requested data. Anticipated data requests from an application may be handled prior to run-time of the application with the requests specifying data attributes. The data resolution node 416 can then obtain the data based on the specified attributes and prepare it for use at run-time when needed. In certain implementations, the data resolution node 416 deconstructs such a resolution request into various requests (“data query requests”) that are proxied to one or of the data source nodes 422, 432, 434, or 442. In certain implementations, the data resolution system provides schema information to one or more of the data consumer nodes 412 or 414 to indicate to their respective applications which data or types of data are available for use.

In certain implementations, the schema node 418 coordinates between all data sources which attributes they host and how a request for a particular system for a single record or multiple records is to be formed. In certain implementations, a master schema is maintained by the same server or servers that host the data resolution node 416. In certain implementations, the schema node 418 maintains two registers for schema management: (1) the schema data itself, and (2) data consumers that utilize the schema data (“schema consumers”). In such implementations, data consumers register data resolution request templates with the data resolution node 416 to allow the data resolution node 416 to record the dependency on data source objects and fields. In certain implementations, a server that hosts the scheme node 418 is not necessarily the system of record for the master schema and schema data, but instead maintains a library of schemas for proxying requests to data source nodes. In other implementations, the server that hosts the schema node 418 stores schema data locally to allow for fast lookups.

In certain implementations, each data source 420, 430, 440, comprises at least one data source node. For example, data sources 420 and 440 is illustrated as hosting a single data source node 422 and 442, respectively, while the data source 430 hosts data source nodes 432 and 434. In certain implementations, one or more of the data source nodes 422, 432, 434, or 442 registers their schemas, providing information including but not limited to attribute namespace, attribute name, user-friendly attribute names and/or groups, and the name of the data source associated with a respective schema. In certain implementations, the data source nodes update the schema node 418 when their schemas change.

In certain implementations, when the data source node 422, for example, registers with the data resolution node 416, it will provide schema data to the schema node 418 to be maintained in a schema repository. In certain implementations, multiple data source nodes may exist at a single data source, which may have already been registered with the data resolution node 416.

In certain implementations, the system topology 400 may be horizontally scaled by adding additional data consumer nodes, data source nodes, or data resolution nodes. In certain implementations, load balancing and configuration management of the system topology 400 may be managed by existing frameworks familiar to those of ordinary skill in the art, such as Apache ZooKeeper.

FIG. 5 is a sequence diagram illustrating data resolution according to some implementations. The data resolution node 416 may act as a registrant of all data sources and data source schemas, as illustrated by registration 510. In certain implementations, if the data resolution node 416 was restarted or a new data resolution node is added to a cluster, the schema would be reloaded from another node or a request to the data source for the schema would be made to a data source node. The data resolution node 416 may expose data source names and data source schemas to the data consumer node 412.

As illustrated by resolution 520, when a data resolution request is received from the data resolution node 412, the data resolution node 416 requests resolution from data sources for each data resolution expression within the data resolution request. In certain implementations, a data resolution request may comprise a data object that comprises data resolution expressions to be resolved. For example, a data resolution request may conform to the following naming convention:

{{<Data Source Name>.<Data Attribute Group>.<Data Attribute Name>}}.

In certain implementations, additional data fields may include IsRequired to indicate the value must resolve correctly, the time-to-live (TTL) which specifies how long a data resolution node should retain the object, and a protocol which indicates the transport protocol. The data resolution node 416 then transmits data source query requests to each of the data source nodes 422, 432, and 442. In certain implementations, data resolution requests that include expressions to be resolved by a single data source are sent in a single data source query request.

Once the data resolution node 416 receives the values for each data resolution expression from the data source nodes 422, 432, and 442, it replaces all expressions in the data object of the data resolution request (i.e., generating a hydrated data object) and returns the results to the data consumer node 412. In certain implementations, the data resolution node 416 stores the object in local cache with the TTL set in the data resolution request. In certain implementations, the data consumer node 412 may indicate in the data resolution request that the data resolution node 416 warm the data and store it in a local cache or an otherwise temporary data store. Once the data is warmed, the data resolution node 416 notifies the data consumer node 412 that the data is prepared and ready for execution. In certain implementations where the data resolution node 416 is located in the same data center as the data consumer node 412, network topology may be configured to ensure optimal data transfer latency.

An illustrative example is now described. In this example, a customer purchases an item from the user. The customer is unsatisfied by the item and posts a negative comment about the transaction on a social media platform. The user desires to send an apology notification to the customer, which would include a first name of the customer, the name of the purchased item, the date of purchase, and an indication of a related product which the customer may prefer or be satisfied with. The first name of the customer is stored on a first data source (“DS1”), the name of the purchased item and the purchase date are stored on a second data source (“DS2”), and the related product data is stored on a third data source (“DS3”). The notification is scheduled to send the message within an hour of the posting of the negative comment on the social media platform. The data consumer (e.g., device of the user) transmits a data resolution request to a data resolution node (e.g., the data resolution node 416 implemented by a data resolution server). The data resolution node transmits a data query request to the respective data sources, which return a response that includes the values for each data field requested. If the data consumer indicated that the data resolution request was only to warm the data, the data resolution node may store the data locally and inform the data consumer that the data is available. The data consumer, when ready to execute the notification send, receives the hydrated data object from the data resolution node and performs the notification send.

While the implementations data resolution have been described herein in the context of enterprise systems, it is contemplated that these implementations may be suitable in applications for that require data management together with or as an alternative to data synchronization.

FIG. 6 is a flow diagram illustrating a method 600 for performing data resolution according to some implementations. The method 600 may be performed by processing logic comprising hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (such as instructions run on a processing device), or a combination thereof. In one implementation, the method 600 may be performed by one or more processing devices associated with a host database system (e.g., implemented on the application server 100).

Referring now to FIG. 6, at block 610, a data resolution request is received by a processing device (e.g., a processing device of the target system 410 implementing the data resolution node 416). The data resolution request comprises a data object that comprises a plurality of data resolution expressions. In some implementations, the data resolution request originates from a data consumer (e.g., and is received via the data consumer node 412). In some implementations, the data resolution request is associated with an application utilized by the data consumer and is implemented at least partially by a data consumer node (e.g., the data consumer node 412). In some implementations, the data resolution request does not include any indication of data sources that are queried by the processing device, and is agnostic as to the sources from which the data will ultimately be received. Such implementations improve overall system efficiency by allowing the data consumer to request data without specifying which sources to obtain the data from.

In some implementations, the data resolution request is received by the processing device prior to runtime of the application. For example, the data resolution request may be received during design time. In some implementations, the data resolution request may be received after design time and before runtime of the application. For example, the data consumer may schedule one or more times for which the data resolution request is to be transmitted to the processing device (e.g., daily, weekly, at a specified time prior to a scheduled runtime of the application, etc.).

In some implementations, the processing device transmits schema data to the data consumer (e.g., via the client node 412) prior to receiving the data resolution request. The schema data may derived or obtained from a schema registry (e.g., which may be managed by the schema node 418). In some implementations, the schema data comprises a set of available expressions of which the plurality of expressions the data resolution request may be a subset. In some implementations, the processing device makes available the plurality of expressions to the data consumer or the application prior to runtime of the application. In some implementations, the data consumer makes available the plurality of expressions to the application prior to runtime of the application. In some implementations, the processing device transmits schema data, or updated schema data, to the data consumer after receiving the data resolution request. For example, the processing device may determine that the data consumer is not using up-to-date schema data, and may transmit updated schema data to the data consumer.

In some implementations, the processing device queries one or of the plurality of data sources, or additional data sources, for schema data. The processing device may then update the schema registry based on schema data received from the data sources.

At block 620, the processing device identifies a plurality of data sources (e.g., one or more of the data sources 420, 430, or 440) based on a schema registry (e.g., which may be managed by the schema node 418). In certain implementations, the schema registry may identify the plurality of data sources by mapping data resolution expressions from the data object to data sources known to be associated with such data resolution expressions.

At block 630, the processing device queries each of the plurality of data sources for data corresponding to the plurality of expressions. At block 640, the processing device receives from the plurality of data sources and generates a hydrated version of the data object comprising the received data. In certain implementations, the hydrated version of the data object is similar to the data object originally received in the data resolution request, except that the data resolution expressions in the various fields of the data object are replaced with the received data. In certain implementations, the hydrated version of the data object is generated prior to runtime of the application.

At block 650, the processing device transmits the hydrated version of the data object to the data consumer. In certain implementations, the hydrated version of the data object is transmitted to the data consumer during or prior to runtime of the application. In some implementations, the hydrated version of the data object is transmitted to the data consumer in response to a runtime request received, by the processing device, from the data consumer or the application.

In the foregoing description, numerous details are set forth. It will be apparent, however, to one of ordinary skill in the art having the benefit of this disclosure, that the present disclosure may be practiced without these specific details. While specific implementations have been described herein, it should be understood that they have been presented by way of example only, and not limitation. The breadth and scope of the present application should not be limited by any of the implementations described herein, but should be defined only in accordance with the following and later-submitted claims and their equivalents. Indeed, other various implementations of and modifications to the present disclosure, in addition to those described herein, will be apparent to those of ordinary skill in the art from the foregoing description and accompanying drawings. Thus, such other implementations and modifications are intended to fall within the scope of the present disclosure.

Furthermore, although the present disclosure has been described herein in the context of a particular implementation in a particular environment for a particular purpose, those of ordinary skill in the art will recognize that its usefulness is not limited thereto and that the present disclosure may be beneficially implemented in any number of environments for any number of purposes. Accordingly, the claims set forth below should be construed in view of the full breadth and spirit of the present disclosure as described herein, along with the full scope of equivalents to which such claims are entitled. 

What is claimed is:
 1. A computer-implemented method comprising: receiving, by a processing device, a data resolution request comprising a data object that comprises a plurality of data resolution expressions; identifying, by the processing device, a plurality of data sources based on a schema registry that maps the plurality of data resolution expressions to schemas associated with each of the plurality of data sources; querying, by the processing device, each of the plurality of data sources for data corresponding to the plurality of data resolution expressions; receiving, by the processing device, the data from the plurality of data sources; generating, by the processing device, a hydrated version of the data object comprising fields populated with the received data; and transmitting, by the processing device, the hydrated version of the data object to a data consumer from which the data resolution request originated.
 2. The computer-implemented method of claim 1, wherein the data resolution request does not include any indication of any of the plurality of data sources for which the processing device queries.
 3. The computer-implemented method of claim 1, wherein the data resolution request is associated with an application utilized by the data consumer, and wherein the data resolution request is received prior to runtime of the application.
 4. The computer-implemented method of claim 3, wherein the hydrated version of the data object is generated before runtime of the application.
 5. The computer-implemented method of claim 4, wherein the hydrated version of the data object is transmitted to the data consumer during runtime of the application.
 6. The computer-implemented method of claim 4, wherein the hydrated version of the data object is transmitted to the data consumer in response to a runtime request received, by the processing device, from the data consumer.
 7. The computer-implemented method of claim 1, further comprising: receiving, by the processing device, schema data from each of the plurality of data sources; and generating or updating, by the processing device, the schema registry to include the received schema data.
 8. The computer-implemented method of claim 1, further comprising: transmitting, by the processing device, the schema data to the data consumer, wherein the schema data comprises the plurality of expressions, and wherein the data consumer is to make available the plurality of expressions to an application utilized by the data consumer prior to runtime of the application.
 9. A database system, comprising: a processing device; and a memory device coupled to the processing device, the memory device having instructions stored thereon that, in response to execution by the processing device, cause the processing device to: receive a data resolution request comprising a data object that comprises a plurality of data resolution expressions; identify a plurality of data sources based on a schema registry that maps the plurality of expressions to schemas associated with each of the plurality of data sources; query each of the plurality of data sources for data corresponding to the plurality of expressions; receive the data from the plurality of data sources; generate a hydrated version of the data object comprising fields populated with the received data; and transmit the hydrated version of the data object to a data consumer from which the data resolution request originated.
 10. The database system of claim 9, wherein the data resolution request does not include any indication of any of the plurality of data sources for which the processing device queries.
 11. The database system of claim 9, wherein the data resolution request is associated with an application utilized by the data consumer, wherein the data resolution request is to be received prior to runtime of the application, and wherein the hydrated version of the data object is to be generated before runtime of the application.
 12. The database system of claim 11, wherein the hydrated version of the data object is to be transmitted to the data consumer during runtime of the application.
 13. The database system of claim 11, wherein the hydrated version of the data object is to be transmitted to the data consumer in response to a runtime request received, by the processing device, from the data consumer.
 14. The database system of claim 9, wherein the instructions further cause the processing device to: generate the schema registry to include schema data received from each of the plurality of sources.
 15. The database system of claim 9, wherein the instructions further cause the processing device to: transmit the schema data to the data consumer, wherein the schema data comprises the plurality of expressions, and wherein the data consumer is to make available the plurality of expressions to an application utilized by the data consumer prior to runtime of the application.
 16. A non-transitory computer-readable storage medium having instructions encoded thereon which, when executed by a processing device, cause the processing device to: receive a data resolution request comprising a data object that comprises a plurality of data resolution expressions; identify a plurality of data sources based on a schema registry that maps the plurality of expressions to schemas associated with each of the plurality of data sources; query each of the plurality of data sources for data corresponding to the plurality of expressions; receive the data from the plurality of data sources; generate a hydrated version of the data object comprising fields populated with the received data; and transmit the hydrated version of the data object to a data consumer from which the data resolution request originated.
 17. The non-transitory computer-readable storage medium of claim 16, wherein the data resolution request does not include any indication of any of the plurality of data sources for which the processing device queries.
 18. The non-transitory computer-readable storage medium of claim 16, wherein the data resolution request is associated with an application utilized by the data consumer, wherein the data resolution request is to be received prior to runtime of the application, wherein the hydrated version of the data object is to be generated before runtime of the application, and wherein the hydrated version of the data object is to be transmitted to the data consumer during runtime of the application in response to a runtime request received from the data consumer.
 19. The non-transitory computer-readable storage medium of claim 16, wherein the instructions further cause the processing device to: generate the schema registry to include schema data received from each of the plurality of sources.
 20. The non-transitory computer-readable storage medium of claim 16, wherein the instructions further cause the processing device to: transmit the schema data to the data consumer, wherein the schema data comprises the plurality of expressions, and wherein the data consumer is to make available the plurality of expressions to an application utilized by the data consumer prior to runtime of the application. 